Pattern
Pattern3mo ago

Staff Data Engineer

IndiaPuneFull-time (Salary)lead
OtherData EngineeringData EngineerStaff Data EngineerData & AI
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Quick Summary

Overview

As a Principal Data Engineer, you’ll be a technical leader and systems thinker within Pattern’s Data Engineering team—designing and scaling our canonical data model to deliver trusted,

Technical Tools
OtherData EngineeringData EngineerStaff Data EngineerData & AI
As a Principal Data Engineer, you’ll be a technical leader and systems thinker within Pattern’s Data Engineering team—designing and scaling our canonical data model to deliver trusted, high-quality data. You’ll transform complex, raw data into tables that are easy to understand and efficient to power analytics, forecasting, and AI/ML with a set of efficient pipelines. You’ll lead through influence, shaping technical direction, mentoring engineers, and building the “single source of truth” that drives Pattern’s global growth.
  • Design and evolve canonical and medallion-layer data models (bronze/silver/gold) that enable scalable, governed data across the organization.
  • Build and optimize ETL/ELT pipelines using Apache Airflow, Spark, Trino, and cloud-native tools.
  • Develop high-performance data marts and semantic layers that serve analytics and data science needs.
  • Architect streaming and analytical systems using Kafka and ClickHouse for real-time and batch insights.
  • Define and enforce standards for data modeling, documentation, quality, and lineage across all domains.
  • Partner with Analytics, AI/ML, and Infrastructure teams to translate business logic into reusable, trusted data assets.
  • Mentor engineers, lead design reviews, and drive continuous improvement in scalability and data reliability.
  • Design and evolve canonical and medallion-layer data models (bronze/silver/gold) that enable scalable, governed data across the organization.
  • Build and optimize ETL/ELT pipelines using Apache Airflow, Spark, Trino, and cloud-native tools.
  • Develop high-performance data marts and semantic layers that serve analytics and data science needs.
  • Architect streaming and analytical systems using Kafka and ClickHouse for real-time and batch insights.
  • Define and enforce standards for data modeling, documentation, quality, and lineage across all domains.
  • Partner with Analytics, AI/ML, and Infrastructure teams to translate business logic into reusable, trusted data assets.
  • Mentor engineers, lead design reviews, and drive continuous improvement in scalability and data reliability.
  • Lead multiple engineering teams or initiatives, providing technical direction, coaching, and feedback to foster growth and high performance.
  • Operate as a cross-team engineer and advisor, proactively identifying opportunities, dependencies, and risks across products and platforms.
  • Drive high-impact architectural and process improvements, reducing technical debt and enabling long-term scalability, resilience, and operational excellence.
  • Represent Data Engineering with executive stakeholders, helping set technical strategy and translating business needs into forward-looking data capabilities.
  • Establish engineering best practices and advocate for robust design, testing, quality, security, and monitoring standards across teams.
  • Lead incident resolution for critical data platform issues, and cultivate a culture of knowledge sharing and blameless postmortems.
  • Evaluate and recommend adoption of emerging technologies where they drive measurable business impact.
  • Scale your impact through effective delegation, enabling teams to deliver autonomously while maintaining technical rigor and clarity.
  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
  • 10+ years of experience in Data Engineering, including 2+ years in a architectural-level technical role.
  • Expertise in SQL, data modeling, and data mart design.
  • Deep hands-on experience with Apache Airflow, dbt, Spark, Kafka, and ClickHouse.
  • Proven experience designing medallion data architectures and scalable data lakehouse solutions.
  • Proficiency in Python or Scala, and familiarity with AWS, GCP, or Azure data ecosystems.
  • Strong understanding of data governance, lineage, and quality frameworks.
  • Demonstrated ability to mentor engineers and influence architectural strategy across teams.
  • Experience with real-time or streaming data (Kafka, Kinesis, or Pub/Sub).
  • Knowledge of data observability and catalog tools (DataHub, Amundsen, Monte Carlo, Great Expectations, or Soda).
  • Experience in eCommerce, retail analytics, or digital marketplaces.
  • Exposure to governed data contracts and semantic layer frameworks.
  • Proven track record of leading data architecture initiatives or cross-functional platform modernization.
  • Contributions to open-source data tools or engagement in data community initiatives

    • Listing Details

    Posted
    January 8, 2026
    First seen
    March 26, 2026
    Last seen
    April 24, 2026

    Posting Health

    Days active
    29
    Repost count
    0
    Trust Level
    25%
    Scored at
    April 24, 2026

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